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History of US Nuclear Forces

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45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Particulate Effluent Characterization (Final Report)

Understanding particulate emissions from nuclear facilities could help differentiate between normal nuclear operations and potential nuclear accidents or nuclear weapons tests. Oak Ridge National Laboratory (ORNL) is unique in that there are several types of nuclear facilities on site: an operating production reactor, radiochemical separation facilities, and a spallation neutron source. This project deployed a high-volume particulate air filter sampler to collect airborne particulate effluent from the nuclear facilities on site at ORNL. Collections occurred regularly from November 1, 2024, through June 30, 2025, and were analyzed via gamma spectroscopy in the laboratory. The radioisotope iodine-123 ( 123 I) was detected in several samples throughout the collection period. Detailed atmospheric transport modeling was performed on all detections for source attribution, and the most likely source of the 123 I was determined to be the Spallation Neutron Source. The project demonstrated the viability of ORNL as a test bed for effluent monitoring studies.

54 ENVIRONMENTAL SCIENCES↗

Responsible Artificial Intelligence for Insider Threat Mitigation

This report examines the application of artificial intelligence (AI) technologies for insider threat mitigation (ITM) programs in nuclear security facilities. Insider threat detection presents unique challenges due to the subtle and adaptive nature of these threats, the complex signatures involved, and the scarcity of available data for analysis. Traditional human-centered approaches, while essential, face limitations in processing large amounts of data continuously and detecting subtle patterns across multiple systems. AI technologies can potentially address these limitations by providing 24/7 monitoring capabilities, identifying complex patterns that might escape human observation, and offering consistent application of security criteria. However, the deployment of AI in nuclear security contexts introduces significant new risks, including workflow disruption, expanded attack surfaces, potential for misuse, and ethical concerns regarding privacy, fairness, transparency, safety, and security. The high-consequence nature of nuclear security decisions demands careful consideration of these risks and systematic approaches to their mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Safeguards Technology Program FY2026 Mid-Year Report for Project WBS# 24.1.3.3: Development of Procedures for Th-U Radiochronometry of Uranium Particles by LG-SIMS

Implementing 230 Th- 234 U radiochronometry of environmental uranium particles by large geometry secondary ion mass spectrometry (LG-SIMS) requires assessment, validation, and technical support before safeguards conclusions can be drawn from the information. This project investigates the most challenging aspects of LG-SIMS particle radiochronometry 230 Th- 234 U measurements through a collaboration between LANL and NIST, to provide best practices and procedures for determining high quality ages with optimized uncertainties. This includes exploration of reducing detector backgrounds, investigating the best ways to report uncertainties, and establishing recommended instrument setups.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Study on Application of Distributed Network of Sensors with List Mode for NMAC Literature Review

Nuclear material accounting and control (NMAC) for nuclear security detects, deters, and resolves questions related to unauthorized removal (i.e. theft) or misuse of nuclear material. NMAC also serves as a key insider threat mitigation measure and aids in recovery of nuclear material that is missing. Effective nuclear security depends on NMAC for timely and accurate information about nuclear material types, quantities, and locations. Bulk nuclear material processing facilities, however, present unique challenges for effective NMAC due to the presence of large quantities of material in-process and the accumulation of residual material holdup within process equipment. These holdup accumulations can obscure accurate physical inventory taking and complicate efforts to resolve NMAC irregularities at the facility level. Bulk material monitoring systems often rely on material balance calculations and indirect measurement techniques, which may mask protracted theft of smaller amounts of nuclear material. These monitoring limitations have generated increased interest in continuous monitoring technologies, including distributed non-destructive assay (NDA) sensor networks capable of providing real-time or near-real-time measurement of material movement and accumulation within bulk processing environments. Recent advancements in distributed networks of NDA radiation detectors and sensing technologies provide an opportunity to address these limitations. Although such distributed sensor networks have been implemented in select facilities for IAEA Safeguards applications, their potential for supporting NMAC functions specifically tailored to nuclear security objectives remains largely unexplored. Furthermore, emerging list-mode data acquisition technologies have reached high technology readiness levels, enabling time-correlated detection of nuclear events across multiple temporal scales. These capabilities provide enhanced opportunities for accurate holdup measurement, continuous process monitoring, and improved detection of material theft or misuse over time. The increasing global expansion of civil nuclear power and development of related bulk material processing facilities, including those supporting high-assay low-enriched uranium (HALEU) and other advanced reactor fuel fabrication, further increases the need for advanced measurement and monitoring strategies for NMAC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Artificial Intelligence for (AI) Nuclear Security: Expert Perspectives on AI Priorities for the Office of International Nuclear Security

Artificial intelligence (AI) has the potential to transform nuclear security operations, offering opportunities to enhance effectiveness while simultaneously introducing new challenges. As AI technologies rapidly evolve, agencies across the United States Government (USG) are researching, implementing, and evaluating various AI models and systems. Given the broad capabilities and applications of these technologies, it is essential for each agency to identify and articulate those areas where it can make meaningful contributions aligned with its mission and expertise. To address this need for strategic focus, in late Fiscal Year 2025 (FY2025), the Office of International Nuclear Security (INS) established an AI Task Force (AITF) to gather input from subject matter experts (SMEs) regarding the most appropriate role INS could serve in researching, evaluating, or implementing AI for nuclear security. The AITF engaged 15 experts from national laboratories with backgrounds in cyber security, physical security, transport security, insider threat mitigation, nuclear engineering, human-systems engineering, and AI/ML development. This white paper summarizes the insights gathered from these SMEs and presents a potential roadmap for INS engagement with AI technologies. The recommendations outlined here are intended to inform INS leadership as they make strategic decisions about resource allocation and program direction in this rapidly evolving technological domain.

97 MATHEMATICS AND COMPUTING↗

Yield Estimates of three Historical Atmospheric Nuclear Explosions at Lop Nor, from Reduced Order Models of Regionally Recorded Rayleigh Waveforms and One Seismic Station: A Brief Communication

We use a reduced order model (ROM) for Rayleigh waveforms sourced by large atmospheric explosions along with data collected from a single seismic station (TLG) to estimate the yields of three atmospheric nuclear tests with order-megaton (MT) yields. These historical tests were conducted by China between 1973 and 1980 (CHIC 15, CHIC 16, and CHIC 26). We use our ROM to estimate yields of 2.34 MT (CHIC 15), 0.51 MT (CHIC 16), and 1.15 (CHIC 26) in the 20.5 s period band that are consistent with publicly accepted values of 3 MT (CHIC 15), 0.50 MT (CHIC 16), and 0.730 MT (CHIC 26).

58 GEOSCIENCES↗

Refining a Novel Process Monitoring Method to Safeguard Continuously Cycling Designs Using Isotopic Ratios

In advanced reactor (AR) designs, a common feature is continuous chemical processing and circulation of the nuclear material. This work bridges a significant measurement gap in safeguarding reactors with circulating fuel or continuous refueling by leveraging and building on the isotope ratio method first developed by our team under an FY21 Advanced Reactors International Safeguards Engagement (ARISE) project (Uribe et al. 2021). In circulating fuel designs, the radioisotope inventory changes from traditional effects (e.g., radioactive decay, fission) but also includes material transport due to pressure and temperature gradients. Such designs may also require regular or continuous additions or removals during operation, which significantly increases the rate of inventory change compared to traditional pressurized water reactor (PWR)s. Thus, directly tracking the nuclear inventory is ineffective since the isotopes are continuously added and removed. The isotope ratio method instead focuses on detecting changes to the input and output flows of radioisotopes. Previous work showed that for well-chosen pairs of isotopes, the isotopic ratio provides a sensitive and lasting indicator of deviation from normal conditions (e.g., startup, shutdown, diversion). The isotope ratio method is a process monitoring method with potential for application in for forward-looking approaches to International Atomic Energy Agency (IAEA) safeguards. The original process monitoring method was developed for a specific case—the decay tank of a thorium-fueled molten salt breeder reactor. In this expanded work, we explored other types of reactors and processes with nonstationary (e.g., flowing) nuclear material, which are difficult to safeguard with traditional methods because of the transient nature of the systems. The goal of the present work is to generalize the isotope ratio method for use in processes with continuously flowing nuclear material. All continuous processes have an average time for isotopes to be replaced in the system. The isotope ratio method works by choosing radioisotopes with half-lives both above and below the processing time. The present work seeks to explore which isotopes are suitable for the method by simulating the nuclear inventory, radioisotope emissions, and detector responses for several classes of advanced reactors. While the method can in principle be applied to other processes (e.g., enrichment or reprocessing facilities), the present work limits scope to ARs with continuously flowing fuel. Section 2 details the mathematics supporting the isotope ratio method, and Section 3 introduces the representative ARs selected for this work. Section 4 discusses how each reactor was analyzed, and Section 5 showcases the results for each representative reactor. Finally, Section 6 provides concluding remarks and suggests pathways for further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Quantification of LEU Holdup using gamma ray imaging and inverse transport solver

Holdup is the residual amount of special nuclear material (SNM) remaining in a processing facility after the bulk materials have been cleaned out. In commercial uranium processing facilities, quantification of holdup is a major challenge because of the highly variable shapes and sizes of the deposits. Any method that attempts to generalize and calibrate deposit shapes in order to quantify holdup will be prone to high uncertainties. Uncertainties on the order of ±50% are typical in holdup results. In international safeguards applications, a ±50% uncertainty can result in a large amount of material unaccounted for (MUF) thereby increasing the difficulty of detecting material diversion and facility misuse. An imaging-based methodology has been developed with the objective of significantly reducing this uncertainty by using the true deposit shape, instead of relying on oversimplified geometric assumptions. The project is a collaboration between ORNL, Y-12, and the University of Tennessee, Knoxville, TN. Uranium sources of known masses were measured using the Germanium Gamma-ray Imager (GeGI), a high-resolution imaging spectrometer, creating a pixelated map for each spectral bin. Two different gamma imaging methods are employed in this work: coded aperture imaging and Compton imaging. A validated MonteCarlo model of the detector has been developed using the GEANT4 code for determining the intrinsic response of the detector, its enclosure, and the coded aperture mask. An inverse transport solver based on the Markov Chain Monte-Carlo approach known as Differential Evolution Adaptive Metropolis (DREAM) is employed to use the measurement data from the image pixels (coded aperture or Compton) to solve for the mass of 235 U in the deposit. A reliable method based on the DREAM solver has been developed to flag the infinite thickness condition of a uranium deposit. The project team is working towards improving the image reconstruction for Compton imaging so that a better localization of the source can be achieved. Besides treating the coded aperture and Compton imaging methods independently, the project is also evaluating a combined method that uses the Compton scatter data from a coded aperture measurement. GEANT4 simulations are being performed to evaluate the combined approach. The impact on the DREAM optimization as the source thickness progressively approaches infinite thickness is being evaluated. A number of uranium sources available at ORNL have been measured, and the DREAM results have been tested and validated for the coded aperture imaging. A similar effort will be carried out to validate the Compton based method once the development of algorithms for better localization are complete. The imaging based quantification is very amenable to unattended monitoring of holdup accumulation at key measurement points. A proof of concept measurement has been completed to demonstrate this capability The current work used the high energy resolution imager GeGI. However, the approach and methodologies are applicable to other imagers such as the cadmium zin telluride (CZT) based imager manufactured by H3D, Inc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Gamma Spectrometry Code Rodeo for Uranium Enrichment—FY 2021 Report

In FY22, the participating Department of Energy (DOE) laboratories continued the work on the project “Gamma Spectrometry Code Rodeo for Uranium Enrichment”. Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL) continued their efforts to acquire spectra using uranium sources. A collimator (with side and back shields) was custom designed and constructed at ORNL. Spectra were acquired at ORNL using the uranium enrichment standards supplied by New Brunswick Laboratory (NBL) and the collimated M400 detector. Spectra were also acquired using steel absorbers of different thickness placed between the source and the collimated M400 detector. The plan was to ship the collimator to LLNL so that spectra could be acquired using the LLNL detector in collimated geometries. This activity was suspended since problems were noticed with the performance of the LLNL M400 detector. Also, it was brought to light to the project team that some of the aspects of the M400 detector had been updated by the vendor H3D in response to requests by the IAEA. In February 2021, the ORNL and LLNL M400 detectors were returned to the H3D factory in order to resolve the problems with the LLNL detector and to update ORNL and LLNL detectors to the same configuration as the M400 supplied to the IAEA. H3D repaired the LLNL M400 and performed the IAEA updates on both the ORNL and LLNL detectors. ORNL and LLNL received the detectors in April 2021. Data acquisition was continued using the upgraded detectors. ORNL re-collected the spectra using point sources and the NBL standards in uncollimated and collimated geometries. The collimator was shipped from ORNL to LLNL. Spectra were acquired at LLNL through Q4 of FY22. When the ORNL spectra were examined closely, it became apparent that there were spurious artifacts present in some of the spectra. This rendered suspect the ORNL spectra collected in June/July 2021 time frame. ORNL contacted H3D and per H3D’s advice, the M400 detector was returned to H3D for repairs in mid-August 2021. H3D diagnosed the problem and established that the root cause was the extra tight packaging that created a strain on the CZT crystals, causing one of them to break down. The repaired M400 was returned to ORNL in early September 2021. ORNL re-started data acquisition for the third time. Data was continued to be acquired at ORNL and LLNL through September 2021. The ORNL and LLNL data will be shared with the principal investigators from the analyzing laboratories. The GADRAS code and FRAM have been developed to have the capability to analyze the M400 spectra. Good quality spectra from FY21 have been analyzed using modified versions of GADRAS and FRAM. The spectra have also been analyzed using the GEM code. The analysis results from GADRAS, FRAM and GEM codes are presented and discussed in this report. Some preliminary results from FRAM and GEM analysis were presented in February 2021 at the U-Pu Isotopics Workshop sponsored by the IAEA. CZTU code is being modified to analyze M400 spectra. Data collection, code development and analysis will be continued in FY22 as per the FY22 Project Work Plan (PWP).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Event Classifications on DNE2 Main Experiment Data using a Convolutional Neural Network Ensemble

The Dynamic Networks (DN) Experiment for FY24 (DNE2) is an experiment within DN with the goal of quantitatively evaluating the effectiveness of solutions developed so far by various researchers under the Low Yield Nuclear Monitoring (LYNM) program using a shared set of metrics and datasets. A key component of this experiment is the mimicking of a signature processing pipeline, and comparing currently accepted and standard-use processing methods to more state-of-the-art processes developed under DN. In this work, we focus specifically on the Event Characterization (EC) Focus Area (FA) of the pipeline, where a seismic event’s magnitude, yield and class are identified. We use Deep Learning (DL) to classify the type of events being processed as either earthquakes (EQs) or explosions (EXs) for three iterations of experiment datasets. The model is noticeably more confident and accurate in classifying explosions than earthquakes, reflecting a known shortcoming of the model, that being of a bias towards predicting explosions over earthquakes in the west coast due to training data biases.

97 MATHEMATICS AND COMPUTING↗

2025 CEA SMAD Digitizer Type Approval Evaluation

Sandia National Laboratories has tested and evaluated an updated SMAD digitizer, developed by the French Alternative Energies and Atomic Energy Commission (CEA). The SMAD digitizers are intended to record sensor output for seismic and infrasound monitoring applications.

47 OTHER INSTRUMENTATION↗

Advanced Reactor Safeguards & Security Program: Cybersecurity Scenarios

The use of digital control systems and automation in advanced nuclear power systems introduces different types of vulnerabilities compared to legacy (i.e. analog) control systems that cyber adversaries can exploit. These vulnerabilities pose a challenge to reactor operators and cyber operations staff due to the dynamic nature of the event in which a human response or a lack of response can potentially evolve into a worsening plant condition. Using the Department of Homeland Security Cyber and Infrastructure Security Agency’s (CISA) critical infrastructure exercise framework, this document presents several cyber security scenarios typical of digital control systems that could be used in advanced reactor designs. These scenarios can be used in tabletop exercises to evaluate cyber security posture or conduct training on different aspects of cyber security, including detection, threat hunting using indicators of compromise, evaluating incident response, risk mitigation, incident reporting, information sharing and recovery.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Unattended Monitoring of Uranium Holdup with Scintillating Fibers

This work evaluated the use of scintillating fiber (SciFi) radiation sensors as a cost-effective, unattended monitoring technique for uranium holdup accumulation in reprocessing equipment. With ruggedized packaging and an outer diameter of less than 1 cm, scintillating fibers offer deployment flexibility. Additionally, plastic scintillating fibers coupled with standard optical fibers provide an affordable option to monitor locations kilometers away from a localized control room or data acquisition (DAQ) system. These combinations of characteristics along with their relatively low manufacturing costs make scintillating fibers ideal for installation at key measurement points such as pipes, valves, and filtration systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Spectrum Unfolding with the MC-15

The Multiplicity Counter 15 tube detector or MC-15 is an optimized detector designed for use in the field. It is composed of 15 3 He tubes embedded in high density polyethylene (HDPE). Recent work has explored expanding the use of the MC-15 beyond multiplicity counting to neutron dosimetry applications. Knowledge of the neutron energy spectrum information is required to use a detector as a neutron dosimeter. The MC-15 tube layout is shown in Figure 1. The unique layout makes it possible to use the detector for neutron spectroscopy via spectrum unfolding. Spectrum unfolding requires (1) energy dependence of the detector response, (2) a detector response matrix that precisely quantifies the response to mono-energetic neutrons, (3) an initial guess spectrum, (4) an unfolding algorithm, and (5) measured data (counts in the case of the MC-15). An energy dependent detector response matrix (DRM) can be constructed by considering either each of the three rows of 3 He tubes as a distinct detector or each individual tube as a distinct detector. The HDPE separating the 3 He in the MC-15 provides the distinct energy dependent response for the rows and individual tubes. In this report we detail the development of detector response matrices for the MC-15 and the application of the Los Alamos Unfolding Code (LUC) to both simulated and measured data. Three MC-15 orientations were studied: (1) standard orientation with the MC-15 front facing the source, (2) standard orientation with Cd sheet, (3) 90° orientation with the side of the MC-15 facing the source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Nuclear Security Risks for HALEU Fuels

There is growing interest in high-assay low-enriched uranium (HALEU) for use in advanced nuclear reactors as a high-energy fuel source. The primary objectives of this report are to identify the security risks that directly result from HALEU and to identify the gaps and challenges it presents from a theft and sabotage perspective. This study focuses on HALEU security risks for the front end of the fuel cycle and includes a review of the supply chain, fuel fabrication, and transport for terrestrial reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗